Where do Kafka persist all its messages?

Apache Kafka is a popular distributed event streaming platform that is designed to handle real-time data streaming at scale. One common question that arises when using Kafka is: where does it persist all its messages? In this article, we will explore the storage mechanisms used by Kafka to ensure durability and fault tolerance.

Persistence in Apache Kafka.

Persistence is one of the key features of Apache Kafka that sets it apart from other messaging systems. Kafka ensures that messages are stored durably and can be consumed by consumers even after they have been processed by the application. This is achieved through the use of storage mechanisms that provide fault tolerance and high availability.

1. Kafka Brokers.

The main component of Kafka responsible for storing messages is the Kafka broker. A Kafka cluster consists of one or more brokers, each of which is responsible for handling a portion of the message data. Brokers store messages in log files called partitions, which are replicated across multiple brokers for fault tolerance.

2. Log Segments.

Each partition in Kafka is divided into segments, which are immutable files that contain messages in the order they were received. As new messages arrive, they are appended to the end of the current segment. Once a segment reaches a certain size or time threshold, it is closed and a new segment is created. This ensures that messages are persisted even in the event of a failure.

3. Replication.

To ensure fault tolerance, Kafka replicates partitions across multiple brokers in a Kafka cluster. Each partition has one leader and one or more followers, which keep a copy of the data synchronized with the leader. If a broker fails, one of the followers can be promoted to become the new leader, ensuring that messages are still accessible.

4. Offsets.

In addition to storing messages, Kafka also maintains a pointer called an offset for each consumer group. Offsets are used to track the progress of consumers in reading messages from a topic. By storing offsets in a designated topic called "__consumer_offsets", Kafka ensures that consumers can resume reading messages from where they left off, even after a restart.

Conclusion.

In conclusion, Apache Kafka persists all its messages by storing them in log segments on Kafka brokers, which are replicated for fault tolerance. By using a distributed architecture and replication mechanisms, Kafka ensures that messages are durable and accessible, even in the face of failures. The combination of log-based storage, replication, and offset tracking makes Kafka a reliable and scalable platform for real-time data streaming.

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